A hybrid approach of artificial neural network and multiple regression to forecast typhoon rainfall and groundwater-level change |
| |
| Authors: | Ping-Cheng Hsieh Wei-An Tong |
| |
| Institution: | 1. Department of Soil and Water Conservation, National Chung Hsing University , Taichung City, Taiwan (R.O.C.)  https://orcid.org/0000-0002-9304-9203;2. Department of Soil and Water Conservation, National Chung Hsing University , Taichung City, Taiwan (R.O.C.) |
| |
| Abstract: | ABSTRACT A forecasting model is developed using a hybrid approach of artificial neural network (ANN) and multiple regression analysis (MRA) to predict the total typhoon rainfall and groundwater-level change in the Zhuoshui River basin. We used information from the raingauge stations in eastern Taiwan and open source typhoon data to build the ANN model for forecasting the total rainfall and the groundwater level during a typhoon event; then we revised the predictive values using MRA. As a result, the average accuracy improved up to 80% when the hybrid model of ANN and MRA was applied, even where insufficient data were available for model training. The outcome of this research can be applied to forecasts of total rainfall and groundwater-level change before a typhoon event reaches the Zhuoshui River basin once the typhoon has made landfall on the east coast of Taiwan. |
| |
| Keywords: | typhoon rainfall forecasting groundwater-level forecasting artificial neural network multiple regression analysis Zhuoshui River basin Taiwan typhoon characteristic data groundwater resources pre-typhoon |
|
![ORCID Icon]({"type":"image","src":"/templates/jsp/images/orcid.png"} "ORCID Icon")
https://orcid.org/0000-0002-9304-9203;2. Department of Soil and Water Conservation, National Chung Hsing University , Taichung City, Taiwan (R.O.C.)